Big Data Analytics and Artificial Intelligence in Electronics

Dear Colleagues,

In big data, the enormous amount of data generated by each industry is typical of ultra-high dimensions, necessitating innovative solutions to discover the required patterns. Big data analysis and intelligent computing solutions are increasingly being used to reduce the complexity and cognitive burden of processing such large amounts of data. Big data analytics is also the focus of data science, meaning that big data is expanding rapidly in every field, such as industry, engineering, healthcare, and so on. The application of advanced analytic techniques to very large, diverse big data sets, which include structured, semi-structured, and unstructured data from various sources and sizes ranging from terabytes to zettabytes, is known as big data analytics. Big data analytics is also critical for modeling and forecasting future outcomes, improving business intelligence, and ultimately fueling faster and better decisions. Big data analytics play an important role in many organizations, such as dealing with massive amounts of data containing critical information, such as cybersecurity, fraud detection, health informatics, intelligence reports for any organization, marketing records, and so on. Optimization, deep learning, machine learning, convolutional neural network (CNN), artificial neural networks (ANN), natural language processing (NLP), support vector machine (SVM), transfer and active learning, data mining, distributed learning, and other AI-based methods can be used for big data analysis.

Furthermore, the integration of big data, the Internet of Things (IoT), and AI has paved the way for a plethora of novel real-world applications. These converged technologies encompass not only information and communication technology, but also various industries such as business, smart farming, industrial automation, and healthcare, to name a few. IoT connects the physical world to the internet and generates massive amounts of big data that must be refined using machine learning and deep learning to extract valuable features. There are also numerous challenges associated with underutilizing the big data generated by IoT devices in terms of machine learning, deep learning, and AI. To address these challenges, it is argued that AI is required for big data analytics.

This Special Issue will concentrate on the most recent advancements in the application of big data analytics and artificial intelligence in electronics. This Special Issue aims to bring together the most recent developments in the aforementioned areas within this framework.

Potential topics of interest include, but are not limited to, the following:

• Big data analytics and big data applications
• Big data artificial intelligence (AI)
• Big data systems
• Deep learning and big data analytics in medical imaging informatics
• Intelligent IoT and IIoT
• Healthcare and medical images security
• Big data in healthcare, medicine big data analytics
• Big data techniques and its applications
• BPNN-based particle swarm optimization in data analysis for transportation big data
• IoT, medical imaging AI systems, and smart wearable body sensors
• Deep learning for healthcare
• Convolutional neural networks (CNN), artificial neural networks (ANN), natural language processing (NLP)
• Deep learning for image/video-based object detection
• Deep learning algorithm/architectures/theory
• Deep learning-based object detection for real-world applications
• Deep learning for secure fingerprint techniques
• Machine learning techniques for propagation modeling and wireless communications

Dr. Inam Ullah
Dr. Rehmat Ullah
Dr. Ateeq Ur Rehman
Prof. Dr. Mohamed Tahar Ben Othman
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.